Hopping gives this tiny robot a leg up
MIT engineers developed an insect-sized jumping robot that can traverse challenging terrains and carry heavy payloads.
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New research could allow a person to correct a robot’s actions in real-time, using the kind of feedback they’d give another human.
With a new design, the bug-sized bot was able to fly 100 times longer than prior versions.
Teaching a robot its limits, to complete open-ended tasks safely
The “PRoC3S” method helps an LLM create a viable action plan by testing each step in a simulation. This strategy could eventually aid in-home robots to complete more ambiguous chore requests.
Daniela Rus named to French National Academy of Medicine
As the Director of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), Rus leads over 1,700 researchers in pioneering innovations to advance computing and improve global well-being.
Can robots learn from machine dreams?
MIT CSAIL researchers used AI-generated images to train a robot dog in parkour, without real-world data. Their LucidSim system demonstrates generative AI’s potential for creating robotics training data.
A faster, better way to train general-purpose robots
Inspired by large language models, researchers develop a training technique that pools diverse data to teach robots new skills.
Combining next-token prediction and video diffusion in computer vision and robotics
A new method can train a neural network to sort corrupted data while anticipating next steps. It can make flexible plans for robots, generate high-quality video, and help AI agents navigate digital environments.
A new algorithm helps robots practice skills like sweeping and placing objects, potentially helping them improve at important tasks in houses, hospitals, and factories.